Recurring Decimal
Machine Learning Engineer
Recurring Decimal, Phoenix, AZ, United States
- Design and implement scalable MLOps supportive data pipelines for data ingestion, processing, and storage.
- Experience deploying models with MLOps tools such as Vertex Pipelines, Kubeflow, or similar platforms along with Vertex AI.
- Experience implementing and supporting end-to-end Machine Learning workflows and patterns. Experience with LangChain or similar orchestrator, Vector DB or similar
- Expert level programming skills in Python and experience with Data Science and ML packages and frameworks.
- Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD practices.
- Experience working with large-scale machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, or related frameworks.
- Experience and knowledge in the most recent advancements in Gen AI, including Gemini, OpenAI, Claud and exposure to open-source Large Language Models (LLMs).
- Experience building AI/ML products using technologies such as LLMs, neural networks and others.
- Experience with RAG and Supervised Tuning techniques.
- Strong distributed systems skills and knowledge.
- Development experience of at least one public cloud provider, Preferably GCP,Google AutoML.
- Excellent analytical, written, and verbal communication skills.